class_docstr: Featurize messages using SpaCy.
docstr: Creates a new component (see parent class for full docstring).
docstr_tok: ["Creates","a","new","component","(","see","parent","class","for","full","docstring",")","."]
code: def create(
      cls,
      config: Dict[Text, Any],
      model_storage: ModelStorage,
      resource: Resource,
      execution_context: ExecutionContext,
  ) -> GraphComponent:
      """Creates a new component (see parent class for full docstring)."""
      return cls(config, execution_context.node_name)
  
imports: import numpy
  import typing
  import logging
  from typing import Any, Text, Dict, List, Type
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.graph import ExecutionContext, GraphComponent
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.featurizers.dense_featurizer.dense_featurizer import DenseFeaturizer
  from rasa.nlu.tokenizers.spacy_tokenizer import SpacyTokenizer
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.constants import SPACY_DOCS, DENSE_FEATURIZABLE_ATTRIBUTES, FEATURIZER_CLASS_ALIAS
  from rasa.shared.nlu.constants import TEXT, FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
  from rasa.utils.tensorflow.constants import POOLING, MEAN_POOLING
label_desc: Use image node_id 5 for calling the SpacyFeaturizer obj's underlying member method code with example usage: obj.create(cls, config, model_storage, resource, execution_context) and returns: cls